Satisfactory Skills Research Articles

Social Interaction Skills in English Communication

Aims: The researchers wanted to determine the relationship between social interaction skills in English communication as the researchers noticed that social interaction using the English language is what professionals usually used. They wanted to discover if the HUMSS students are prepared to move up to the next step, which is going to higher education.
 Study Design: The design used in this study is Descriptive research.
 Place and Duration of Study: Laguna University Senior High School Department.
 Methodology: Grade 12 Humanities and Social Sciences students of Laguna University - Senior High School Department consisting forty-two (42) students were the chosen respondents of the researchers.
 Results: There is a significant relationship between the students’ English proficiency and social interaction skills as the results showed that most of the respondents fall under upper intermediate on the English proficiency test. In addition to that, English language in social communication is essential as it helps them to socialize with other people resulting in a very satisfactory skill.
 Conclusion: There is a significant relationship between the students’ English proficiency and social interaction skills.

Deterministic Forecasting and Probabilistic Post‐Processing of Short‐Term Wind Speed Using Statistical Methods

AbstractThere is a great need for an accurate short‐term wind speed forecast, and statistical forecasts have gained increased popularity for their computational efficiency and satisfactory skill. However, there has been no systematic research to fully explore the capabilities of statistical approaches and evaluate the applicability of probabilistic information from statistical ensemble. This study first compares the skills of different statistical methods, based on linear regression, machine learning (ML), and deep learning (DL), using three strategies (i.e., direct, recursive, and multi‐output) against the three operational numerical models and their bias‐corrections, for short‐term wind speed forecast over Pearl River Estuary during 2018–2021. Inter‐comparison between statistical forecasts reveals the dominant superiority of direct strategy. On this basis, Random Forest (RF) and Support Vector Machines (SVM) perform best compared to other statistical forecasts and bias correction of numerical forecasts throughout 48 hr lead time, while the performance of methods with simplified (linear) or more complex (DL) model structures degrades significantly. Moreover, the top 10 forecasts are utilized to account for forecast uncertainties but present a substantial under‐dispersed prediction. Two traditional methods and three modern methods are implemented to perform probabilistic post‐processing. Modern methods based on ML or DL present worse skills, while traditional methods, particularly for ensemble model output statistics, show added value in discriminating binary events due to limited enhancements in calibration. Overall, RF and SVM using direct strategy are highly recommended for short‐term wind speed forecasts, and efforts are ongoing to address the issues of strong wind prediction and ensemble calibration.

Learning curve of ultrasound-guided surgeon-administered transversus abdominis plane (UGSA-TAP) block on a porcine model

BackgroundSurgeons commonly perform ultrasound-guided Transversus Abdominis Plane blocks to manage acute pain following abdominal surgeries. There is no consensus on whether surgeons should undergo basic hands-on training to perform TAP blocks or if video-based learning is sufficient. We theorized that simulation-based learning is superior to video-based learning. In the present study, we present the analysis of technical skills of UGSA-TAP block performance on a live porcine model by general surgery trainees after undergoing video or simulation-based learning. MethodsWe performed a prospective, double-blinded, randomized study. Ten surgery residents and two surgery critical-care fellows (n = 12) without prior experience in performing the TAP block were recruited. The participants were randomized either into a video-based or simulation-based training group. After that, all participants performed a TAP block on a live anesthetized pig, which was recorded and scored by three blinded anesthesiologists. All participants completed a post-performance survey to assess their confidence in gaining competency in the UGSA-TAP block. Statistical analyses were performed to assess the differences between the two groups. P < 0.05 was considered statistically significant. ResultsAll simulation-based learning participants successfully performed a survey scan, identified the three muscular layers of the abdominal wall, and identified the transversus abdominis plane compared to 50 %, 50 %, and 33 % video-based learning group participants for the respective parameters (p < 0.05). While some performance metrics showed no statistically significant differences between the groups, substantial effect sizes (Cohen's ℎ up to 1.07) highlighted notable differences in participants' performance. Both groups exhibited confidence in core competencies, with varied rates of satisfactory skill execution. Performance assessed using a global rating scale revealed a higher passing rate for the simulation group (83 % vs. 33 %). Participant feedback via the Likert scale reflected confidence post-training. Inter-rater reliability (0.83–1) confirmed the robustness of study evaluations. ConclusionThe UGSA-TAP block curriculum should be introduced into the surgical residency programs with an emphasis on simulation-based learning to enhance the procedural skills of the trainees before transitioning to surgical patients.

Data reformation – A novel data processing technique enhancing machine learning applicability for predicting streamflow extremes

Hydrologists have been actively exploring the utility of machine learning (ML) models for predicting streamflow. While ML methods have proven to be as accurate as conventional modeling techniques for streamflows well represented in the training set, they continue to lack satisfactory skills for extreme events. In this study, a novel ‘data reformation’ technique is proposed based on the Relative Strength Index (RSI) – a measure of speed and direction of changes in the time series. RSI homogenizes all observations to a constrained 0–100 range, and all ‘out-of-sample’ data in the testing set fall within the space of the training set. Long Short-Term Memory network with an attention mechanism is used to train three ML models using 55,055 events from the CAMELS dataset (670 basins, 1980–2014). Predictions are made for 12,424 events, of which 3,810 are significantly higher than streamflows in the training set. The ML model based on RSI-reformed data exhibits superior performance, as compared to other advanced ML models without data reformation. Peaks up to 15 times larger than those in the training events are accurately predicted, leading to an outperforming model skill for 433 out of 670 catchments. These findings indicate that incorporating a new data reformation technique into the data pre-processing step in ML modeling can enhance the utility of ML models for extreme events. This research encourages further exploration to identify better data reformation methods to enable confident ML predictions.

Uncertainty estimation for a new exponential-filter-based long-term root-zone soil moisture dataset from Copernicus Climate Change Service (C3S) surface observations

Abstract. Soil moisture is a key variable in monitoring climate and an important component of the hydrological, carbon, and energy cycles. Satellite products ameliorate the sparsity of field measurements but are inherently limited to observing the near-surface layer, while water available in the unobserved root-zone controls critical processes like plant water uptake and evapotranspiration. A variety of approaches exist for modelling root-zone soil moisture (RZSM), including approximating it from surface layer observations. While the number of available RZSM datasets is growing, they usually do not contain estimates of their uncertainty. In this paper we derive a long-term RZSM dataset (2002–2020) from the Copernicus Climate Change Service (C3S) surface soil moisture (SSM) COMBINED product via the exponential filter (EF) method. We identify the optimal value of the method's model parameter T, which controls the level of smoothing and delaying applied to the surface observations, by maximizing the correlation of RZSM estimates with field measurements from the International Soil Moisture Network (ISMN). Optimized T-parameter values were calculated for four soil depth layers (0–10, 10–40, 40–100, and 100–200 cm) and used to calculate a global RZSM dataset. The quality of this dataset is then globally evaluated against RZSM estimates of the ERA5-Land reanalysis. Results of the product comparison show satisfactory skill in all four layers, with the median Pearson correlation ranging from 0.54 in the topmost to 0.28 in the deepest soil layer. Temporally dynamic product uncertainties for each of the RZSM product layers are estimated by applying standard uncertainty propagation to SSM input data and by estimating structural uncertainties in the EF method from ISMN ground reference measurements taken at the surface and at varying depths. Uncertainty estimates were found to exhibit both realistic absolute magnitudes and temporal variations. The product described here is, to the best of our knowledge, the first global, long-term, uncertainty-characterized, and purely observation-based product for RZSM estimates up to 2 m depth.

Digital competences of teachers in the use of YouTube as an educational resource: analysis by educational stage and gender

The purpose of this study was to analyze the digital competence of teachers on the use of YouTube as a didactic resource in the teaching and learning process of students. Specifically, this was analyzed and compared for each educational stage (Preschool Education, Primary Education, Secondary Education, Adult Education, and Vocational Education-VET) between genders of the teacher (female and male). For this, an ex post facto non-experimental design was used, with a sample of 2157 in-service teachers from all over Spain. Among the main results found in this study, teachers of all educational stages had satisfactory skills on the use of YouTube to search and communicate information, although low in relation to the creation of audio-visual material through YouTube. In addition, it was evidenced how gender was a significant factor which affected the competencies of teachers, in most of the educational stages analyzed.

Effects of a structural simulation curriculum for the repair of obstetrical anal sphincter injuries.

To assess the short-term and skill-retention effects of a structural simulation curriculum for the repair of obstetrical anal sphincter injuries (OASIS). This prepost experimental study recruited 31 obstetrics and gynecology residents from Peking Union Medical College Hospital. OASIS repair skill evaluations (at all timepoints) comprised a task-specific checklist (TSC), global rating scale (GRS), and pass/fail grade. A beef-tongue model was adopted in the simulation curriculum. After baseline testing, residents completed a structured 1-h workshop. Two weeks later, a second test was performed, followed by a one-to-one teaching workshop, with the proper completion of a checklist as the end-point. Three months later, residents completed a third test. The overall pass rate at baseline was 16.1%, with higher GRS scores (p= 0.035) in senior residents. Additionally, previewing the procedure before class and a history of OASIS repair observation were associated with higher TSC and GRS scores. Significant skill improvement was observed in the second and third tests, with pass rates of 96.8% and 93.5% respectively. Both TSC and GRS scores were improved compared with baseline (p< 0.001). A structural simulation curriculum integrating deliberate practice under supervision improves OASIS repair competence and achieves satisfactory skill retention.

A Decentralized Approach for Modeling Organized Convection Based on Thermal Populations on Microgrids

AbstractIn this study, a spectral model for convective transport is coupled to a thermal population model on a two‐dimensional horizontal “microgrid,” covering the typical gridbox size of general circulation models. The goal is to explore new ways of representing impacts of spatial organization in cumulus cloud fields. The thermals are considered the smallest building block of convection, with thermal life cycle and movement represented through binomial functions. Thermals interact through two simple rules, reflecting pulsating growth and environmental deformation. Long‐lived thermal clusters thus form on the microgrid, exhibiting scale growth and spacing that represent simple forms of spatial organization and memory. Size distributions of cluster number are diagnosed from the microgrid through an online clustering algorithm, and provided as input to a spectral multiplume eddy‐diffusivity mass flux scheme. This yields a decentralized transport system, in that the thermal clusters acting as independent but interacting nodes that carry information about spatial structure. The main objectives of this study are (a) to seek proof of concept of this approach, and (b) to gain insight into impacts of spatial organization on convective transport. Single‐column model experiments demonstrate satisfactory skill in reproducing two observed cases of continental shallow convection. Metrics expressing self‐organization and spatial organization match well with large‐eddy simulation results. We find that in this coupled system, spatial organization impacts convective transport primarily through the scale break in the size distribution of cluster number. The rooting of saturated plumes in the subcloud mixed layer plays a key role in this process.

Evaluating wind speed and power forecasts for wind energy applications using an open-source and systematic validation framework

Building on the verification and validation work developed under the Second Wind Forecast Improvement Project, this work exhibits the value of a consistent procedure to evaluate wind power forecasts. We established an open-source Python code base tailored for wind speed and wind power forecast validation, WE-Validate. The code base can evaluate model forecasts with observations in a coherent manner. To demonstrate the systematic validation framework of WE-Validate, we designed and hosted a forecast evaluation benchmark exercise. We invited forecast providers in industry and academia to participate and submit forecasts for two case studies. We then evaluated the submissions with WE-Validate. Our findings suggest that ensemble means have reasonable skills in time series forecasting, whereas they are often inferior to single ensemble members in wind ramp forecasting. Adopting a voting scheme in ramp forecasting that allows ensemble members to detect ramps independently leads to satisfactory skill scores. Throughout this document, we also emphasize the importance of using statistically robust and resistant metrics as well as equitable skill scores in forecast evaluation.

Intraseasonal scale ensemble forecasts of precipitation and evapotranspiration for the Madeira River basin using different physical parameterizations

Eta Regional Model of CPTEC-INPE is used to obtain intraseasonal (30-day) 8-member ensemble forecasts over the Madeira River basin for the period 2002–2012. The initial and boundary conditions are taken from Atmospheric General Circulation Global Model in six members and from Global Coupled Ocean-Atmosphere Model in two members. The intraseasonal forecasts produced by dynamic downscaling with Eta Regional model ensemble have satisfactory skill. The skill of the ensemble mean is better than the individual members up to 15-days lead time forecasts. The ensemble mean reproduces the seasonal cycle and spatial distribution of the hydrological variables. Members with the relaxation technique of Betts-Miller-Janjic produced better results. The forecasts by the members that used Kain-Fritsch scheme presented larger deviations from observations. Substantial improvements in skill are obtained through bias correction. This is the first work to attempt dynamic downscaling over the Madeira Basin in the intraseasonal time scale for a period of 10 years. The ensemble downscaled products have potential to be fed into surface hydrological models for forecasting droughts and floods and related hydrological variables over the basin.

Handler Proficiency (Nahkoda) Dnature Operationalize Purse Saine Fishing Gear

This study aims to: (1) find out the skills of handlers in operating purse seine fishing gear (2) Knowing the fishing ground of purse seine fishing gear (3) Knowing the factors that affect fishing operations with purse seine fishing gear. The research methods used are survey methods, interviews and questionnaires. The data were analyzed descriptively. A total of 30 purse seine handlers at PPP Lampulo have been respondents in this study. The results showed that the purse seine ship handlers in Lampulo PPP are mostly 41-50 years old, the average handler education level is junior high school, the majority of handlers in Lampulo PPP have more than 5 years of experience, handlers at Lampulo PPP only have a Certificate of Proficiency (SKK) in operating ships. Generally, purse seine boat handlers at PPP Lampulo have satisfactory skills when viewed from how to determine fishing grounds, search for fish swarms, collect schools of fish and operating techniques for fishing gear.

Development of a Learning Support System for Blood Sampling Techniques Using a Magnetic Motion Capture System

Blood sampling requires a particularly dexterous technique; the existing training system is not sufficient for students to acquire satisfactory skills by the time they graduate. Hence, we have developed a learning support system for blood sampling techniques that can present the difference in the angle between a teacher's syringe and surface of patient's skin while blood sampling and angle between a student's syringe and the surface of skin in real time. In this system, students can learn blood sampling techniques by imitating a teacher's motions presented by computer graphics and moving their own syringe until the displayed angle difference becomes zero. This system is useful for learning to insert syringes at the same angle as the teacher. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

A study to assess the knowledge and skills of Accredited Social Health Activists and its retention after training in community-based primary eye care.

Purpose:Community volunteers like Accredited Social Health Activists (ASHAs) could be utilized for linking community and eye care services. Research is needed to effectively utilize them. This study was to assess whether ASHAs could imbibe new knowledge in eye care and conduct vision screening.Methods: Settings and Design:A pre-post-intervention study in South Delhi Integrated Vision Centres. It was conducted from January 2016 to March 2017. One day of conceptual training followed by hands-on training in vision screening was imparted to ASHAs. The knowledge was assessed thrice: before, immediately after, and following 1 year after training. The vision screening skill was assessed twice. Descriptive analysis using percentages, mean and standard deviations. Paired t-test was used for assessing the change in scores.Results:A total of 102 ASHAs were recruited. A significant increase in the knowledge score of ASHAs before (14.96) and after training (25.38) (P < 0.001) was noted. The knowledge score was sustained at 1 year (21.75). The satisfactory skill of vision screening was seen in 88 (86.3%) ASHAs after training, while 79 (77.5%) ASHAs still retained it after 1 year.Conclusion:The potential to involve ASHAs in community-based frontline eye care activities: awareness generation of eye diseases, identification of referrable conditions, and facilitating individuals to seek eye care facilities. This study informs about the duration, frequency, and content of the training. It also provides evidence on the improvement and sustainability of eye care knowledge and skills by ASHAs after conceptual and hands-on training.

Robust Meteorological Drought Prediction Using Antecedent SST Fluctuations and Machine Learning

AbstractWhile reliable drought prediction is fundamental for drought mitigation and water resources management, it is still a challenge to develop robust drought prediction models due to complex local hydro‐climatic conditions and various predictors. Sea surface temperature (SST) is considered as the fundamental predictor to develop drought prediction models. However, traditional models usually extract SST signals from one or several specific sea zones within a given time span, which limits full use of SST signals for drought prediction. Here, we introduce a new meteorological drought prediction approach by using the antecedent SST fluctuation pattern (ASFP) and machine learning techniques (e.g., support vector regression (SVR), random forest (RF), and extreme learning machine (ELM)). Three models (i.e., ASFP‐SVR, ASFP‐ELM, and ASFP‐RF) are developed for ensemble, probability, and deterministic drought predictions. The Colorado, Danube, Orange, and Pearl River basins with frequent droughts over different continents are selected, as the cases, where standardized precipitation evapotranspiration index (SPEI) are predicted at the 1° × 1° resolution with 1‐ and 3‐month lead times. Results show that the ASFP‐ELM model can effectively predict space‐time evolutions of drought events with satisfactory skills, outperforming the ASFP‐SVR and ASFP‐RF models. Our study has potential to provide a reliable tool for drought prediction, which further supports the development of drought early warning systems.

Relationships Between the Typhoon‐Induced Wind and Waves in the Northern South China Sea

AbstractWind‐wave interactions have been broadly investigated for their great implications on air‐sea momentum transfer, whereas our knowledge on those forced by typhoons (hurricanes) is still limited. Accordingly, relationships between wind and wave characteristics were analyzed using observations on the northern South China Sea during four typhoons. An empirical wind‐wave model was proposed for typhoon‐induced wind seas which exhibits satisfactory skills in predicting significant wave heights (). Meanwhile, typhoon‐forced wind‐wave relation was investigated using the wave growth function. By delineating the relationship between the dimensionless and peak wave period scaled with 10 m and friction wind velocities, simplified functions for the growing and steady wind seas were proposed, respectively. However, great misalignment could occur owing to the contamination of swells resulting from the typhoon's slow translation speed, as well as the extremely short or long radial distance from typhoon centers, indicating the necessity of considering typhoon structures in screening swell influences.

English

BACKGROUND Basic life support (BLS) although a lifesaving skill, is seldom taught in the first year of traditional Indian undergraduate medical curriculum resulting in lack of competence and confidence. Medical Council of India’s new competency based undergraduate curriculum stresses on early skill acquisition. Basic life support hands-on workshop can be a simple yet effective educational intervention in achieving the goal. The aim of the study is to determine the effectiveness of introduction of BLS training workshop to first year MBBS curriculum as a part of foundation course skills development. METHODS An interventional study in the form of BLS workshop consisting of lecture, demonstration and hands on practice on mannequins was conducted on first MBBS students. Assessment was done by standardized pre- and post-test questionnaire and direct observation of procedural skills (DOPS). Student’s perception was qualitatively explored by conducting focus group discussions (FGD) followed by thematic analysis. RESULTS Analysis of median pre- and post-test scores using Wilcoxon test matched pairs signed rank test revealed highly significant gain in knowledge and confidence (P value = 0.000). Thirty three percent students could perform all the seven steps of cardiopulmonary resuscitation (CPR) correctly, meeting all six quality indicators indicating satisfactory skill acquisition. Six overarching themes emerged from the focus group responses viz. importance of clinical skill acquisition in first year, suggested methods to improve skill training, effectiveness of BLS workshop, usefulness of learning BLS skill, readiness to perform CPR in real life scenario and need for curriculum reformation. CONCLUSIONS Simulation-based hands-on workshop can serve as an effective teaching learning strategy for foundation course BLS skills development under new competencybased first MBBS curriculum by Medical Council of India (MCI). KEYWORDS Basic Life Support, Cardiopulmonary Resuscitation, MBBS, Curriculum, Competency, Qualitative Analysis, Medical Education

Awareness of Nurses’ Working in Health Centers and Health Offices Regarding Communication Skills

Background: The lack of effective communication can lead to misunderstanding, poor performance,interpersonal conflict, ineffective program development, medical mistakes, and many otherundesirable outcomes. This study aimed to assess awareness of nurses’ working in health centersand health offices regarding communication skills. Research design: A descriptive research designwas utilized to conduct this study. Setting: The study was conducted in all health centers and healthoffices in Benha City. Sampling: Convenient sample was used in study which included all thenurses’ work at health centers and health offices in Benha City, the total number of nurses were 124nurses. Tools: Three tools were used in this study: I- A structured interviewing questionnaire toassess nurses’ socio- demographic characteristics, nurses’ knowledge regarding communication skillsand factors affecting nurses’ skills regarding communication. II-The second tool: Likert scale toassess nurses’ attitude regarding communication skills III-The third tool: Observational checklist toassess skills of nurses regarding communication. Results: More than two fifths of studied nursingaged 45 years or more with the mean age 41.97±9.88 years, more than two thirds of nurses had goodknowledge about communication skills, the most factors highly affected communication skills werephysiological factors of internal confusion, factors enhancing in communication and the principles toovercome communication barrier, more than three quarters of studied nurses had positive attitudetoward personal communication and had satisfactory skills about communication. Conclusion: Therewas a statistically significant relation between nurses’ total knowledge with their socio- demographiccharacteristics regarding their marital status and work setting, there was a statistically significantrelation between nurses’ total skills score and their socio- demographic characteristics regarding theirmarital status. There were highly positive correlation between total knowledge with total factors ofstudied nurses and there was no a statistically relation with total skills and total attitude.Recommendation: Develop and implement health educational program for nurses at health centersand health offices to improve nurses’ knowledge and practice regarding communication skills andbooklets should be available and distributed in all health care centers to all nurses about thecommunication and ways to over comes the barriers faced

Resources needed to teach midwife sonographers to measure cervical length with transvaginal ultrasound in the second trimester

Sir, General screening of singleton pregnancies for preterm delivery by adding cervical length measurement with transvaginal ultrasound to second-trimester routine fetal ultrasound examination has been advocated.1 Reference ranges of cervical length are available from 11 to 40 weeks of gestation.2 In the Nordic countries, second-trimester routine ultrasound examinations are performed by specially trained midwife sonographers, and if screening for preterm delivery were to be introduced, cervical length measurements would be done by them. Therefore, we wanted to estimate the resources needed to train midwife sonographers to measure cervical length with transvaginal ultrasound and the time needed for cervical length measurement. One midwife sonographer with 2 years of experience with transvaginal ultrasound but no experience with cervix measurements was trained to measure cervical length by a doctor experienced in obstetric and gynecological ultrasound. After she completed her training, she trained five other midwife sonographers. The number of pregnant women that needed to be examined to acquire satisfactory skills and the time spent in each teaching examination (teacher actively helping the trainee) and training examination (independent examination by the trainee with results compared with those of the teacher) were recorded. The median duration of a teaching examination was 16 minutes (8-48 minutes) and that of a training examination was 14 minutes (7-41 minutes). The median number of women that needed to be examined to complete the training satisfactorily was 47 (range 13-114). The most time-consuming was the recruitment of pregnant volunteers for the teaching and training examinations, which were all performed in the second trimester. During the teaching and training period, both the teacher and the trainee were freed from other clinical work, so that they were readily available to examine the volunteers when they appeared. A centralized teaching and training approach might be more effective and would guarantee uniform learning. Based on our experience, assuming that one out of four women who attend for a second-trimester ultrasound scan volunteers for a teaching-training examination and about 50 women need to be examined for a midwife sonographer to become qualified to measure cervical length, the learning period can be expected to be at least 2 weeks in a unit with 100 routine second-trimester scans per week. If both teacher and trainee are midwife sonographers, the cost would correspond to 1 month’s salary of a midwife sonographer. Two of our trained midwives added cervical length measurement to their routine second-trimester scans (177 scans) and documented the time for the vaginal and abdominal examination separately. The median duration of the abdominal routine fetal scan was 18 minutes (8-46 minutes), and that of the vaginal examination of the cervix was 7 minutes (2-30 minutes). We estimate that adding cervical length measurement to the routine second-trimester scan would extend total scanning time by 5-10 minutes. If the cervical length measurement were to be performed as a separate examination, each examination slot should probably be at least 15 minutes. Our findings could be helpful for estimating the need for resources if screening for preterm delivery using cervical length measurement in conjunction with routine second-trimester ultrasound is considered, and for cost-effectiveness analysis of such a policy.

WRF Simulations of Extreme Rainfall over Uganda’s Lake Victoria Basin: Sensitivity to Parameterization, Model Resolution and Domain Size

Rainfall extremes have strong connotations to socio-economic activities and human well-being in Uganda’s Lake Victoria Basin (LVB). Reliable prediction and dissemination of extreme rainfall events are therefore of paramount importance to the region’s development agenda. The main objective of this study was to contribute to the prediction of rainfall extremes over this region using a numerical modelling approach. The Weather Research and Forecasting (WRF) model was used to simulate a 20-day period of extremely heavy rainfall that was observed in the March to May season of 2008. The underlying interest was to investigate the performance of different combinations of cumulus and microphysical parameterization along with the model grid resolution and domain size. The model output was validated against rainfall observations from the Tropical Rainfall Measuring Mission (TRMM) using 5 metrics; the rainfall distribution, root mean square error, mean error, probability of detection and false alarm ratio. The results showed that the model was able to simulate extreme rainfall and the most satisfactory skill was obtained with a model setup using the Grell 3D cumulus scheme combined with the SBU_YLin microphysical scheme. This study concludes that the WRF model can be used for simulating extreme rainfall over western LVB. In the other 2 regions, central and eastern LVB, its performance is limited by failure to simulate nocturnal rainfall. Furthermore, increasing the model grid resolution showed good potential for improving the model simulation especially when a large domain is used.

Gauging the performance of CMIP5 historical simulation in reproducing observed gauge rainfall over Kenya

Abstract The detrimental impacts of climate change have drawn the interest of many climate scientists toward understanding the past climate for the sake of preparing for the future. The current study evaluates the performance of 12 rainfall models available in Coupled Model Intercomparison Project Phase 5 (CMIP5) in reproducing observed rainfall over Kenya from 1979 to 2005. Several statistical metrics were deployed in quantifying the disparities between CMIP5 models, in situ, and the Global Precipitation Climatology Centre (GPCC v7) rainfall datasets. The results show satisfactory skill of CMIP5 models' in simulating the bimodal rainfall regime despite exhibiting dry (wet) bias during March–May (MAM) and October–November (OND) season, respectively. The models' skills in reproducing the interannual variability is relatively weak. However, majority of the models captures the temporal pattern with reasonable skills in OND than in MAM and annual rainfall. The impacts of Indian Ocean Dipole (IOD) and El Nino southern oscillation (ENSO) are marked in observed OND rains with no significance link in MAM rains. Overall, CMIP5 models' skills in replicating the mean statistics and teleconnection links are relatively weak. Remarkably, the performance of models at different time scale, metrics, simulation of dynamical and teleconnection patterns are inconsistent among models. Nevertheless, based on skill score, the models are listed from top to bottom as; MPI-ESM-MR, CSIRO-MK3-6-0, GISS-E2-R, MRI-CGCM2.3.3, EC-EARTH, MIROC-ESM-CHEM, FGOALS-g2, BCC-CSM1.1-M, HADGEM-AO, CanESM2, GFDL-ESM2G, IPSL-CM5A-MR, and MME model. This study sheds light on the use of statistical metrics and teleconnection pattern to rank CMIP5 models and forms basis on model selection. Model parameterization over tropics is prudent, and bias correction is paramount in future projections and impacts studies.